Description

Statistics and Health Care Fraud: How to Save Billions helps the public to become more informed citizens through discussions of real world health care examples and fraud assessment applications. The author presents statistical and analytical methods used in health care fraud audits without requiring any mathematical background. The public suffers from health care overpayments either directly as patients or indirectly as taxpayers, and fraud analytics provides ways to handle the large size and complexity of these claims.

The book starts with a brief overview of global healthcare systems such as U.S. Medicare. This is followed by a discussion of medical overpayments and assessment initiatives using a variety of real world examples. The book covers subjects as:

• Description and visualization of medical claims data

• Prediction of fraudulent transactions

• Detection of excessive billings

• Revealing new fraud patterns

• Challenges and opportunities with health care fraud analytics

Dr. Tahir Ekin is the Brandon Dee Roberts Associate Professor of Quantitative Methods in McCoy College of Business, Texas State University. His previous work experience includes a working as a statistician on health care fraud detection. His scholarly work on health care fraud has been published in a variety of academic journals including International Statistical Review, The American Statistician, and Applied Stochastic Models in Business and Industry. He is a recipient of the Texas State University 2018 Presidential Distinction Award in Scholar Activities and the ASA/NISS y-Bis 2016 Best Paper Awards. He has developed and taught courses in the areas of business statistics, optimization, data mining and analytics. Dr. Ekin also serves as Vice President of the International Society for Business and Industrial Statistics.

Table of Contents

1 Health Care Systems and Fraud

Overview

Health care systems

Worldwide health care insurance programs

Medical overpayments

Why health care fraud? Why now?

Impact and importance of fraud assessment

Types and examples of health care fraud

General fraud assessment framework and initiatives

Key takeaways

Additional resources

2 Describing Health Care Claims Data

Overview

Health care data

Understanding health care claims data

Data pre-processing

Descriptive statistical analysis

Discussion

Key takeaways

Additional resources

3 Sampling and Overpayment Estimation

Overview

Sampling and overpayment estimation

Sampling procedures

A closer look at stratified sampling

Overpayment estimation

Discussion

Key takeaways

Additional resources

4 Predicting Health Care Fraud

Overview

Health care fraud analytics

Predictive methods

Prediction of overpayment amount and fraud probability

Classification of health care claims

Accuracy and validation

Discussion

Key takeaways

Additional resources

5 Discovery of New Fraud Patterns

Overview

Outlier detection: Finding excessive billings

Clustering: Grouping health care claims

Association: Finding links among claims

Effectiveness of the analytical methods

Deployment via rules

Current efforts

Key takeaways

Additional resources

6 Challenges, Opportunities and Future Directions

Overview

Shareholders: putting a face on fraudsters and victims

Challenges with payment and fraud control systems

Organizational issues: "No news is good news!"

Evolution of fraud and adaptive fraudsters

Different sides of the coin: Data as a blessing, data as a curse

Legal concerns: Embracing uncertainty

A take on future

Key takeaways

Additional resources

Bibliography

Index

About the Author

Dr. Tahir Ekin is the Brandon Dee Roberts Associate Professor of Quantitative Methods in McCoy College of Business, Texas State University. His previous work experience includes a working as a statistician on health care fraud detection. His scholarly work on health care fraud has been published in a variety of academic journals including International Statistical Review, The American Statistician, and Applied Stochastic Models in Business and Industry. He is a recipient of the Texas State University 2018 Presidential Distinction Award in Scholar Activities and the ASA/NISS y-Bis 2016 Best Paper Awards. He has developed and taught courses in the areas of business statistics, optimization, data mining and analytics. Dr. Ekin also serves as Vice President of the International Society for Business and Industrial Statistics.

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